Amazon announced a raft of improvements to its databases at its AWS Summit in San Francisco, ranging from accelerators for DynamoDB to the ability to query exabytes of unstructured data directly in S3 storage.

There are two improvements to DynamoDB, Amazon's NoSQL database service that is part of AWS. The performance can now be improved using Amazon DynamoDB Accelerator (DAX). This is a fully managed, highly available, in-memory cache for DynamoDB that Amazon says will improve the performance by up to ten times, even at millions of requests per second.

DAX means developers don't need to manage cache invalidation, data population, or cluster management. It can be deployed using a few clicks and turns DynamoDB response times from milliseconds to microseconds. DAX is currently available in preview.

The second improvement for DynamoDB announced at the summit is the ability to access DynamoDB from Amazon Virtual Private Clouds using VPC endpoints. This means you can choose whether to have all network traffic between your application and DynamoDB traverse the public Internet or stay within the AWS cloud. DynamoDB already provides data protection and security using TLS endpoints for encryption-in-transit and a client-side encryption library. The addition of VPC Endpoints for DynamoDB is designed for applications with strict compliance and audit requirements, or that handle sensitive data.

The preview of Amazon Aurora PostgreSQL-Compatible Edition has been made public. As we reported in December, this edition of Aurora provides high durability, high availability, and the ability to quickly create and deploy read replicas while being PostgreSQL compatible.

Improvements were announced for yet another of Amazon's databases at AWS, this time for AWS Redshift. Redshift was designed to give AWS users a way to create petabyte-scale data warehouses. It is optimized for complex queries (often involving multiple joins) across large tables. The new announcement at AWS Summit was a preview of Redshift Spectrum. This is a new tool that will let you use the Redshift analytics and SQL syntax to analyze unstructured data stored in Amazon Simple Storage Service (Amazon S3). Essentially, it avoids the need to load and transform data from your local data warehouse into Redshift. You can also run queries that span both the frequently accessed data stored locally in Amazon Redshift and your full data sets stored cost-effectively in Amazon S3.

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